It is desired to have an efficient solution to find rotational variations between consecutive video frames or between image pairs. Such may be applied to blur determination and compensation, panorama creation, image stabilization and/or object tracking to list just a few examples among many more. Alternate solutions based on mutual information include Hough transforms, Radon transforms, Fourier transforms, and Polar transforms. However, it is desired to have a more efficient solution, as these alternate solutions are resource intensive.
A common problem in panorama creation, e.g., is the occurrence of rotation between two frames which are to be stitched or otherwise joined together. An alternative is to use high accuracy rotation estimation and resample the image before stitching which is computationally expensive and requires a large amount of memory. It is desired to have an application for panorama creation in a camera that corrects for and/or detects rotation before stitching or joining adjacent image segments.
Image rotation generally involves extra computation and processing time rendering it difficult to pull off in real time. Image re-sampling to compensate for rotation before images are stitched is slow and computationally expensive.